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Leaf mechanical resistance in plant trait databases: comparing the results of two common measurement methods

Enrico, Lucas, Díaz, Sandra, Westoby, Mark, Rice, Barbara L.
Annals of botany 2016 v.117 no.1 pp. 209-214
biogeochemical cycles, data collection, databases, ecosystems, equations, leaves, mechanical properties, plant veins, prediction, Australia
Background and Aims The influence of leaf mechanical properties on local ecosystem processes, such as trophic transfer, decomposition and nutrient cycling, has resulted in a growing interest in including leaf mechanical resistance in large-scale databases of plant functional traits. ‘Specific work to shear’ and ‘force to tear’ are two properties commonly used to describe mechanical resistance (toughness or strength) of leaves. Two methodologies have been widely used to measure them across large datasets. This study aimed to assess correlations and standardization between the two methods, as measured by two widely used apparatuses, in order to inter-convert existing data in those global datasets. Methods Specific work to shear (WSS) and force to tear (FT) were measured in leaves of 72 species from south-eastern Australia. The measurements were made including and excluding midribs. Relationships between the variables were tested by Spearman correlations and ordinary least square regressions. Key Results A positive and significant correlation was found between the methods, but coefficients varied according to the inclusion or exclusion of the midrib in the measurements. Equations for prediction varied according to leaf venation pattern. A positive and significant (r = 0·90, P < 0·0001) correlation was also found between WSS values for fresh and rehydrated leaves, which is considered to be of practical relevance. Conclusions In the context of broad-scale ecological hypotheses and used within the constraints recommended here, leaf mechanical resistance data obtained with both methodologies could be pooled together into a single coarser variable, using the equations provided in this paper. However, more detailed datasets of FT cannot be safely filled in with estimations based on WSS, or vice versa. In addition, WSS values of green leaves can be predicted with good accuracy from WSS of rehydrated leaves of the same species.